Impact of COVID-19 pandemic and anti-pandemic measures on tuberculosis, viral hepatitis, HIV/AIDS and malaria–A systematic review

COVID-19 pandemic puts an enormous strain on health care systems worldwide and may have a detrimental effect on prevention, treatment and outcomes of tuberculosis (TB), viral hepatitis, HIV/AIDS and malaria, whose ending is part of the United Nations 2030 Agenda for Sustainable Development. We conducted a systematic review of scientific and grey literature in order to collect wide-ranging evidence with emphasis on quantification of the projected and actual indirect impacts of COVID-19 on the four infectious diseases with a global focus. We followed PRISMA guidelines and the protocol registered for malaria (CRD42021234974). We searched PubMed, Scopus, preView (last search: January 13, 2021) and websites of main (medical) societies and leading NGOs related to each of the four considered infectious diseases. From modelling studies, we identified the most impactful disruptions; from surveys and other quantitative studies (based e.g. on surveillance or program data), we assessed the actual size of the disruptions. The identified modelling studies warned about under-diagnosis (TB), anti-retroviral therapy interruption/decrease in viral load suppression (HIV), disruptions of insecticide-treated nets (ITN) distribution and access to effective treatment (malaria), and treatment delays and vaccination interruptions (viral hepatitis). The reported disruptions were very heterogeneous both between and within countries. If observed at several points in time, the initial drops (partly dramatic, e.g. TB notifications/cases, or HIV testing volumes decreased up to -80%) were followed by a gradual recovery. However, the often-missing assessment of the changes against the usual pre-pandemic fluctuations hampered the interpretation of less severe ones. Given the recurring waves of the pandemic and the unknown mid- to long-term effects of adaptation and normalisation, the real consequences for the fight against leading infectious diseases will only manifest over the coming years.

HIV: HIV OR HIV-1 Hepatitis: hepatitis OR hepatides OR HBV Malaria: malaria OR malariae OR malarias B. Search strategy for grey literature S1

C. Post-hoc amendments to the study protocol
For surveys, we accepted an implicit comparator, i.e. questions with wording "due to COVID-19", or "under current travel restrictions".
In the case of HIV, we adopted the following two additional exclusion criteria: • small sample size: 20 or fewer respondents if not speaking on behalf of programmes or organizations, • surveys in which a certain group of people was asked about the COVID-19 impact on another group (e.g. health care professionals were asked about the impact on patients).
We also did not consider survey questions regarding anticipated difficulties due to COVID-19, as opposed to experienced difficulties.

D. Details of the screening process and the "near-misses" Tuberculosis
Three publications classified as near misses in the full-text screening. Two did not contain data related to COVID-19 [1,2], one did not provide a comparator for the absolute impact [3].

HIV/AIDS
In full-text screening, we excluded 14 full-texts under the label: insufficient reporting/data. Here we give their details. Three [4][5][6] did not contain any precise quantifications in their statements. They reported endangered ART supplies in Indonesia [4], maintaining HIV therapy among people with substance use disorder in Ukraine [6] and cessation of community HIV testing in Birmingham, Alabama [5]. Four publications [7][8][9][10] did not contain information to which period exactly the reported data refer. They reported a decrease in PEP prescriptions (China) [8], interruptions in medication uptake(China) [9], no interruption in outpatient services and therapy withdrawal(Italy) [7] and self-reported problems to access HIV medication by 4% of respondents (Argentina) [10]. Further, four publications were based on surveys of and about individuals with 20 and fewer respondents, reporting no interruptions to HIV care(USA) [11] or no interruptions to access to ART(USA) [12], a decrease in PrEP usage(USA) [13] and reasons preventing the uptake of facility-based HIV testing(Uganda) [14]. Further, two publications did not provide a clear comparison of their observed Toolkit for patient associations, e.g., on how to communicate COVID-information to patients and how to advocate for better treatment of liver disease patients (for media). EASL-ESCMID Position Statement on clinical care for patients, e.g., how healthcare providers can reduce transmission and prioritise patients, links to published research, covered by our systematic search (COVID risk and mortality among patients liver disease/viral hepatitis).coinfection www.aasld.org Several Webinars on COVID-19 and liver disease (management, guidance, treatment, clinical insights and case studies); perspectives on impacts for hepatitis care and personal reports including impact on liver transplantation (US).personal reports and experiences www.worldhepatitisalliance.org Webinars with statements from individuals on COVID-19 and the liver and link to a EASL/WHO discussion on the potential impact of COVID-19 on civil society-delivered hepatitis services and patients.no evidence on the actual impact Member survey on COVID-19 pandemic effects on hepatitis services and patients (results included in the extracted data); accessed 30th September, 2020 Medical advice for individuals living with hepatitis and being infected with COVID-19.coinfection www.HepVoices.org News/information on community pharmacy that has postponed a HCV service from April 2020 to September 2020, but no impact measure stated: https://hepvoices.org/2020/08/hepatitis-cservice-delayed-by-covid-19-to-launch-on-september-1/, accessed 28th January 2021 Reference to a summary of statements received from some US health departments on experiences, concerns, requests, and strategies for STI care, incl. viral hepatitis. It was reported that programs have reduced or suspended services and activities in response to COVID-19 due to reduced staff. Also mentioned: suspension of outreach, education, and prevention; clinic closures, reductions in clinical services. https://www.naccho.org/blog/articles/lhd-hiv-sti-andhepatitis-programs-respond-and-adapt-to-covid- 19. Redirected from HepVoices.org, accessed 28th January 2021.no numerical information Reference to a press article on reduction in HBV-birth doses in India " 19

E. Risk-of-bias assessment tools
We used three different tools for the risk of bias (RoB) assessment according to the type of study. For modelling studies, the tool is based on [29] and we added questions (inspired by [30]) assessing the reporting of the model and sources of data informing the model parameters (S1 Table C). For surveys, we made a minor adjustment to the Risk of Bias Instrument for Cross-Sectional Surveys of Attitudes and Practices [31] based on ideas in [32,33], see S1 Table D. Finally, for other quantitative studies, we compiled the RoB tool from ideas in Appendices F, G in [34], covering two aspects of external and internal validity each, and including an assessment of possible selective reporting (S1 Table E).  Fig. A shows the risk-of-bias assessment of surveys related to hepatitis, tuberculosis and malaria. Surveys related to HIV are assessed in S1 Fig. B. RoB assessment of other studies concerning hepatitis and tuberculosis is shown in S1 Fig. C, and concerning malaria and HIV in S1 Fig. D. As to modelling studies, the main reason for concerns was the missing uncertainty analysis (for HIV [35][36][37][38], for malaria [35,37,39], for tuberculosis [35,40], for viral hepatitis [41]). Two studies did not used a dynamic model ( [37] for HIV, [41] for viral hepatitis). One preprint for HIV [42] did not contain a sufficient description of the model and underlying data sources, but the results seemed to be extended and later published in [43]. Similarly, the description of the data sources behind the model for tuberculosis used in [35] did not clearly state to what extent real world data and official records were utilized. Note that the empty grey circles in case of HIV mean "not applicable". Note that representativeness is assessed with respect to the global picture and is therefore high if only single centre results are reported.

G. Tuberculosis
Here we show the detailed findings quantifying the indirect impact of COVID-19 on TB. S1 Fig. E shows how the numbers of notifications changed in Americas and Europe. An overview of all the identified studies with respect to the outcome and the type of evidence or of data sources is shown in S1 Table F. Further tables detail the impact of COVID-19 on TB notifications(S1 Table G), TB-related clinical outcomes(S1 Table H), and TB-related service provision(S1 Table I), as well as the projected impact on excess cases and deaths from the modelling studies(S1 Table J Week 1 -17 in 2019 Week 1-17 in 2020 Week 1-17: -3.5% (-3.7% to -3.4%) Week 1-9: -5.8% (-6.0% to -5.5%) 67  Only a single comparison, no information on the usual variation of the number of records.

I. Malaria
Here we present overview of the results mapping the indirect impact of COVID-19 on malaria as summarized in the main text. S1 Table N shows an overview of all included studies with respect to reported outcomes, considered population and geographical area. Further tables compare projected and observed malaria cases (S1 Table O), projected and observed malaria deaths (S1 Table P) and the modelled impact of interruption of different malaria prevention measures and the observed interruptions (S1 table Q). S1 Table N : Overview of studies related to malaria with respect to various characteristics. Note that one study [37] reported both observational and modelled data. Shown are also general trends observed within the studied country/region: increase (↑), decrease (↓), changes in both directions (↕). / /

S1 table Q Projected consequences of interruption of malaria prevention measures on malaria cases and deaths and overview of observed disruptions of the measures.
Outcome

Modelling studies Observational studies/reports/surveys Prevention measures
• Interruption of mosquito net distribution campaigns causes the largest increase in malaria case numbers and malaria deaths (considered as a single measure) [35,98].
• Reduction of access to effective malaria therapy causes the strongest increase in the number of malaria cases and the number of malaria deaths (considered as a single measure) [100,101].
• The more prevention measures are reduced or interrupted at the same time, the greater the increase in the number of malaria cases [35,98,100,101].
• The more prevention measures are simultaneously reduced or interrupted in the modelling, the greater the increase in malaria deaths [35,39,98,100,101].
• Modelling COVID-19 pandemic control scenarios: if restrictions are implemented for 12 months, there is the highest increase in malaria deaths if health systems are poorly managed [35,98].
• The more the COVID-19 pandemic can be contained, the more mosquito nets can be distributed, the lower the malaria transmission [99].
• Reduction in health services could lead to a reduction in intermittent malaria prophylaxis in pregnancy [39].

J. HIV/AIDS
In this section we present additional figures and findings related to the indirect impact of COVID-19 on HIV prevention and treatment. S1 Fig. F details reported reduction in HIV testing volumes and changes in positivity rates, all numerical values used in the plot can be found in S1 Table U. S1 Fig. G reports on changes in pre-exposure prophylaxis (PrEP) and S1 Fig. H in post-exposure prophylaxis (PEP). Further, S1 Table S collects the self-reported disruption in HIV services. Finally, to provide detailed numbers to the endpoints discussed in the paper, S1 Table T details all the findings related to ART initiations, ART retention and engagement in care and S1 Table V collects results of the modelling studies. In addition, assuming 20% loss to follow-up for 6 months and a subsequent return to 1990 mortality levels, with equal mortality across age-groups, and a 55% decline in ART initiations led to 475 319 excess DALYs(disability adjusted life-years) lost for Uganda [37]. For comparison, 405 100 excess DALYs were predicted for 20% incidence of COVID-19 and age-related mortality based on that of China. Please note that the tables are organised according to outcomes, so the same reference may appear several times.
A. Changes in facility-based HIV testing volumes. Shown are the % and absolute decrease in the number of HIV tests. Note that using the mean of Jan-Feb 2020 as the baseline does not account for possible seasonality. The WHO declared COVID-19 to be a pandemic on March 11, 2020, whereas in China the lockdown measures were introduced already in late January 2020. The 85% reduction reported by Krakower et al in April 2020 relates to HIV testing on PrEP and can be compared to 59% of 189 PrEP prescribers in the USA reporting skipping HIV testing on PrEP refill [148]. B. Percent change in HIV testing volumes as read off the plots reported by UNAIDS [135]. In this case the comparison is made to the average of Jan-Feb 2020, so the results may be confounded by seasonality. For example, if we calculate the same percent change for March-August 2019 relative to the average of Jan-Feb 2019 from data reported for one centre in Liege, Belgium [141], we would obtain a decrease between 7.5 to 20% for the whole period.
C. Positivity rate as observed by the different studies in 2020 and 2019. Shown are the point estimates and 95% confidence intervals based on the Agresti-Coull method for binomial proportions.

S1 Fig. F Reported reduction in HIV testing volumes and changes in the positivity rate.
The underlying numbers can be found in S1 Table U.
PrEP S1 Fig. G shows the self-reported decrease in usage of PrEP and difficulties accessing PrEP. The main reasons for stopping PrEP in Brazil were impediments with refill (47%), followed by sex abstinence (40%). In all other studies the main reason for stopping or reducing PrEP seemed to be a lower perceived HIV risk/decrease in sexual activities with casual partners. Problems accessing PrEP as a reason for stopping were reported only by 7% [156] , 8% [148], 11% [157]. A single centre in Boston [147] reported a decline in PrEP patients, PrEP initiations and a large increase in PrEP refill lapses compared to the mean of January-February 2020(3188 patients, 107 initiations, 141.5 lapses). Namely, in March 2020, there were 2% fewer patients, 44% fewer initiations and 44% more lapses, whereas in April 2020, there were 6% fewer patients, 68% fewer initiations and 187% more lapses. From Australia, a 24% decrease in the mean weekly number of prescriptions (Apr-June 2020 vs Jan 2019-March 2020) was reported [154] and a specific programme in South Africa observed a 68% increase in the rate of missed PrEP visits of pregnant women (from 34% of missed visits pre-lockdown to 57% of missed visits during lockdown) [153].  [159] commented that the numbers started to increase even before the lockdown was at the end, which is what Chow et al. [160] observed as well.

Other prevention services
Compared to the mean outreach contacts of 5016 in 3 centres in Kenya [140] in Jan-Feb 2020, the programme registered a decrease of 2%(March 2020), 30%(April 2020) and 13%(May 2020) in the outreach contacts. Similarly, an assisted partner notification programme in the same country observed a decrease of 8%(March 2020) and of 36%(Apr 2020) in female index enrolments as compared to the monthly mean of 160 enrolments in Jan-Feb 2020, across two centres involved [166]. Regarding VMMC, countries reported decreased numbers of circumcisions in April, May, June [167] than in January 2020(most notably Lesotho, South Africa, Mozambique, Botswana and Zimbabwe). Without any quantification, another report of UNAIDS [135] mentions that by late 2020, the VMMC programmes in Kenya, Rwanda, Botswana and South Africa were returning to normal.
Disruption and uptake of HIV services in general S1 Table S shows the self-reported service interruptions. In addition, a decrease of overall outpatients visits was noted by several authors: a decrease of 64% in the second quarter of 2020 in Japan [113], of around 60% in both March-April 2020 and May-June 2020 in one centre in Greece [152], always compared to the corresponding period in 2019. In Croatia, the weekly mean went from 46(February 2020) to 22.5(March 2020) [133]. In contrast, an immediate increase in the mean visits/clinic /day of 8.0 (95%CI: 2.3-13.7) following the introduction of level 5 lockdown was observed in KwaZulu Natal [161]. This increase was followed by a slight steady decrease until the start of level 4 lockdown, when another stepwise increase of 11 visits/clinic/day (95% CI: 4.2 -17.8) was observed. Without being specific about the qualitative assessment, as of June 1, 2020, The Global Fund reported 18% of 106 countries experiencing high to very high disruption to HIV services, and 66% experiencing moderate disruptions [54]. The situation seemed to improve only very slightly, with still 55% experiencing moderate disruptions in December [165].